PNAD Contínua - TRIMESTRE
Dados: 2012 - 2024 (Rio Grande do Sul)
Dados: 2012 - 2024 (Rio Grande do Sul)
Fernanda Kelly R. Silva | www.fernandakellyrs.com
26/11/2025
---
title: "PNAD Contínua - TRIMESTRE" # Título do relatório
subtitle: "**Dados: 2012 - 2024 (Rio Grande do Sul)**"
author: "Fernanda Kelly R. Silva | www.fernandakellyrs.com"
lang: pt
date: "`r format(Sys.Date())`"
date-format: short
toc: true
format:
html:
embed-resources: true
#css: ["custom.css"]
code-fold: false
code-tools: true
theme:
light: cosmo
dark: superhero
#title-block-banner: "#874a9c"
code-annotations: hover
execute:
warning: false
message: false
echo: false
---
```{r}
options(timeout = 600)
```
```{r}
#| echo: false
#| warning: false
#| message: false
# install.packages("PNADcIBGE")
# install.packages("survey")
library(PNADcIBGE)
library(survey)
library(foreign)
library(srvyr)
library(reactable)
library(purrr)
```
# 2012
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2012_completo.RData")
```
```{r}
dadosPNADc2012_completo <- dadosPNADc2012_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2012_completoPR <- dadosPNADc2012_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2012_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2012_completoPR)
dadosPNADc2012_completoSRPR <- srvyr::as_survey(dadosPNADc2012_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2012_completoSEC <- dadosPNADc2012_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2012_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2012_completoSEC)
dadosPNADc2012_completoSRSEC <- srvyr::as_survey(dadosPNADc2012_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2012 <- dadosPNADc2012_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2012 <- dadosPNADc2012_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2012_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2012_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2012 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2012_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2012_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2012 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2012_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2012_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2012 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2013
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2013_completo.RData")
```
```{r}
dadosPNADc2013_completo <- dadosPNADc2013_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2013_completoPR <- dadosPNADc2013_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2013_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2013_completoPR)
dadosPNADc2013_completoSRPR <- srvyr::as_survey(dadosPNADc2013_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2013_completoSEC <- dadosPNADc2013_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2013_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2013_completoSEC)
dadosPNADc2013_completoSRSEC <- srvyr::as_survey(dadosPNADc2013_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2013 <- dadosPNADc2013_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2013 <- dadosPNADc2013_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2013_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2013_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2013 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2013_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2013_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2013 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2013_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2013_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2013 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2014
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2014_completo.RData")
```
```{r}
dadosPNADc2014_completo <- dadosPNADc2014_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2014_completoPR <- dadosPNADc2014_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2014_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2014_completoPR)
dadosPNADc2014_completoSRPR <- srvyr::as_survey(dadosPNADc2014_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2014_completoSEC <- dadosPNADc2014_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2014_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2014_completoSEC)
dadosPNADc2014_completoSRSEC <- srvyr::as_survey(dadosPNADc2014_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2014 <- dadosPNADc2014_completoSRPR %>%
dplyr::filter(VD4032 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4032,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2014 <- dadosPNADc2014_completoSRSEC %>%
dplyr::filter(VD4033 != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(VD4033,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2014_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2014_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2014 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2014_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2014_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2014 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2014_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(VD4032, VD4033, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2014_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2014 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2015
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2015_completo.RData")
```
```{r}
dadosPNADc2015_completo <- dadosPNADc2015_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
#ANO 2015 USAR:
dplyr::mutate(V4039C = base::ifelse(is.na(V4039C),
VD4032,
V4039C),
V4056C = base::ifelse(is.na(V4056C),
VD4033,
V4056C)) %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2015_completoPR <- dadosPNADc2015_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2015_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2015_completoPR)
dadosPNADc2015_completoSRPR <- srvyr::as_survey(dadosPNADc2015_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2015_completoSEC <- dadosPNADc2015_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2015_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2015_completoSEC)
dadosPNADc2015_completoSRSEC <- srvyr::as_survey(dadosPNADc2015_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2015 <- dadosPNADc2015_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2015 <- dadosPNADc2015_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2015_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2015_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2015 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2015_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2015_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2015 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2015_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2015_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2015 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2016
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2016_completo.RData")
```
```{r}
dadosPNADc2016_completo <- dadosPNADc2016_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2016_completoPR <- dadosPNADc2016_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2016_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2016_completoPR)
dadosPNADc2016_completoSRPR <- srvyr::as_survey(dadosPNADc2016_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2016_completoSEC <- dadosPNADc2016_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2016_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2016_completoSEC)
dadosPNADc2016_completoSRSEC <- srvyr::as_survey(dadosPNADc2016_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2016 <- dadosPNADc2016_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2016 <- dadosPNADc2016_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2016_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2016_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2016 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2016_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2016_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2016 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2016_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2016_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2016 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2017
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2017_completo.RData")
```
```{r}
dadosPNADc2017_completo <- dadosPNADc2017_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2017_completoPR <- dadosPNADc2017_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2017_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2017_completoPR)
dadosPNADc2017_completoSRPR <- srvyr::as_survey(dadosPNADc2017_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2017_completoSEC <- dadosPNADc2017_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2017_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2017_completoSEC)
dadosPNADc2017_completoSRSEC <- srvyr::as_survey(dadosPNADc2017_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2017 <- dadosPNADc2017_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2017 <- dadosPNADc2017_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2017_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2017_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2017 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2017_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2017_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2017 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2017_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2017_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2017 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2018
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2018_completo.RData")
```
```{r}
dadosPNADc2018_completo <- dadosPNADc2018_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2018_completoPR <- dadosPNADc2018_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2018_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2018_completoPR)
dadosPNADc2018_completoSRPR <- srvyr::as_survey(dadosPNADc2018_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2018_completoSEC <- dadosPNADc2018_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2018_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2018_completoSEC)
dadosPNADc2018_completoSRSEC <- srvyr::as_survey(dadosPNADc2018_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2018 <- dadosPNADc2018_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2018 <- dadosPNADc2018_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2018_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2018_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2018 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2018_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2018_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2018 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2018_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2018_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2018 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2019
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2019_completo.RData")
```
```{r}
dadosPNADc2019_completo <- dadosPNADc2019_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2019_completoPR <- dadosPNADc2019_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2019_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2019_completoPR)
dadosPNADc2019_completoSRPR <- srvyr::as_survey(dadosPNADc2019_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2019_completoSEC <- dadosPNADc2019_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2019_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2019_completoSEC)
dadosPNADc2019_completoSRSEC <- srvyr::as_survey(dadosPNADc2019_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2019 <- dadosPNADc2019_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2019 <- dadosPNADc2019_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2019_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2019_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2019 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2019_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2019_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2019 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2019_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2019_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2019 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2020
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2020_completo.RData")
```
```{r}
dadosPNADc2020_completo <- dadosPNADc2020_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2020_completoPR <- dadosPNADc2020_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2020_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2020_completoPR)
dadosPNADc2020_completoSRPR <- srvyr::as_survey(dadosPNADc2020_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2020_completoSEC <- dadosPNADc2020_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2020_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2020_completoSEC)
dadosPNADc2020_completoSRSEC <- srvyr::as_survey(dadosPNADc2020_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2020 <- dadosPNADc2020_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2020 <- dadosPNADc2020_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2020_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2020_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2020 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2020_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2020_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2020 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2020_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2020_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2020 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2021
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2021_completo.RData")
```
```{r}
dadosPNADc2021_completo <- dadosPNADc2021_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2021_completoPR <- dadosPNADc2021_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2021_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2021_completoPR)
dadosPNADc2021_completoSRPR <- srvyr::as_survey(dadosPNADc2021_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2021_completoSEC <- dadosPNADc2021_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2021_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2021_completoSEC)
dadosPNADc2021_completoSRSEC <- srvyr::as_survey(dadosPNADc2021_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2021 <- dadosPNADc2021_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2021 <- dadosPNADc2021_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2021_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2021_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2021 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2021_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2021_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2021 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2021_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2021_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2021 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2022
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2022_completo.RData")
```
```{r}
dadosPNADc2022_completo <- dadosPNADc2022_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2022_completoPR <- dadosPNADc2022_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2022_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2022_completoPR)
dadosPNADc2022_completoSRPR <- srvyr::as_survey(dadosPNADc2022_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2022_completoSEC <- dadosPNADc2022_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2022_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2022_completoSEC)
dadosPNADc2022_completoSRSEC <- srvyr::as_survey(dadosPNADc2022_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2022 <- dadosPNADc2022_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2022 <- dadosPNADc2022_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2022_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2022_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2022 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2022_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2022_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2022 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2022_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2022_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2022 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2023
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2023_completo.RData")
```
```{r}
dadosPNADc2023_completo <- dadosPNADc2023_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2023_completoPR <- dadosPNADc2023_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2023_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2023_completoPR)
dadosPNADc2023_completoSRPR <- srvyr::as_survey(dadosPNADc2023_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2023_completoSEC <- dadosPNADc2023_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2023_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2023_completoSEC)
dadosPNADc2023_completoSRSEC <- srvyr::as_survey(dadosPNADc2023_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2023 <- dadosPNADc2023_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2023 <- dadosPNADc2023_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2023_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2023_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2023 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2023_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2023_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2023 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2023_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2023_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2023 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2024
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc2024_completo.RData")
```
```{r}
dadosPNADc2024_completo <- dadosPNADc2024_completo %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc2024_completoPR <- dadosPNADc2024_completo %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2024_completoPR <- PNADcIBGE::pnadc_design(dadosPNADc2024_completoPR)
dadosPNADc2024_completoSRPR <- srvyr::as_survey(dadosPNADc2024_completoPR)
```
### Total de Pessoas
```{r}
table_1P_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc2024_completoSEC <- dadosPNADc2024_completo %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc2024_completoSEC <- PNADcIBGE::pnadc_design(dadosPNADc2024_completoSEC)
dadosPNADc2024_completoSRSEC <- srvyr::as_survey(dadosPNADc2024_completoSEC)
```
### Total de Pessoas
```{r}
table_1S_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2024 <- dadosPNADc2024_completoSRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2024 <- dadosPNADc2024_completoSRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc2024_completo %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc2024_completo %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2024 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc2024_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc2024_completo %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2024 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc2024_completo %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc2024_completo %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2024 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# 2025
```{r}
load(file = "C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/Dados_completos/Trimestre/dadosPNADc1VISITA_25.RData")
```
```{r}
dadosPNADc1VISITA_25 <- dadosPNADc1VISITA_25 %>%
dplyr::filter(UF == "Rio Grande do Sul") %>%
dplyr::mutate(cod_SCN_PR = dplyr::case_when(V4013 %in% c("01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4013 %in% c("05000","06000","07001","07002","08001",
"08002","08009","09000") ~ 2,
V4013 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4013 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4013 %in% c("41000","42000","43000") ~ 5,
V4013 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4013 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4013 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4013 %in% c("64000","65000","66001","66002") ~ 9,
V4013 == "68000" ~ 10,
#######################################################
V4013 %in% c("55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4012 == "Trabalhador doméstico" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregado do setor privado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Empregador" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Conta própria" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4012 == "Trabalhador familiar não remunerado" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
########################################################
V4013 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4012 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4012 == "Empregado do setor público (inclusive empresas de economia mista)" & V4013 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4013 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
) %>%
dplyr::mutate(cod_SCN_SEC = dplyr::case_when(V4044 %in% c(
"01101","01102","01103","01104","01105",
"01106","01107","01108","01109","01110",
"01111","01112","01113","01114","01115",
"01116","01117","01118","01119","01201",
"01202","01203","01204","01205","01206",
"01207","01208","01209","01401","01402",
"01500","01999","02000","03001","03002") ~ 1,
V4044 %in% c("05000","06000","07001","07002","08001","08002","08009","09000") ~ 2,
V4044 %in% c("10010","10021","10022","10030","10091",
"10092","10093","10099","11000","12000",
"13001","13002","14001","14002","15011",
"15012","15020","16001","16002","17001",
"17002","18000","19010","19020","19030",
"20010","20020","20090","21000","22010",
"22020","23010","23091","23099","24001",
"24002","24003","25001","25002","26010",
"26020","26030","26041","26042","27010",
"27090","28000","29001","29002","29003",
"30010","30020","30030","30090","31000",
"32001","32002","32003","32009","33001","33002") ~ 3,
V4044 %in% c("35010","35021","35022","36000","37000","38000","39000") ~ 4,
V4044 %in% c("41000","42000","43000") ~ 5,
V4044 %in% c("45010","45020","45030","45040","48010",
"48020","48030","48041","48042","48050",
"48060","48071","48072","48073","48074",
"48075","48076","48077","48078","48079",
"48080","48090","48100") ~ 6,
V4044 %in% c("49010","49030","49040","49090","50000",
"51000","52010","52020","53001","53002") ~ 7,
V4044 %in% c("58000","59000","60001","60002","61000","62000","63000") ~ 8,
V4044 %in% c("64000","65000","66001","66002") ~ 9,
V4044 == "68000" ~ 10,
###################################################################
V4044 %in% c(
"55000","56011","56012","56020","69000",
"70000","71000","72000","73010","73020",
"74000","75000","77010","77020","78000",
"79000","80000","81011","81012","81020",
"82001","82002","82003","82009","90000",
"91000","92000","93011","93012","93020",
"94010","94020","94091","94099","95010",
"95030","96010","96020","96030","96090",
"97000") ~ 11,
V4043 == "Trabalhador doméstico" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregado do setor privado" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Empregador" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Conta própria" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
V4043 == "Trabalhador não remunerado em ajuda a membro do domicílio ou parente" & V4044 %in% c("85011","85012","85013",
"85014","85021", "85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 11,
####################################################################
V4044 %in% c("84011","84012","84013","84014","84015","84016","84017","84020") ~ 12,
V4043 == "Militar do exército, da marinha, da aeronáutica, da polícia militar ou do corpo de bombeiros militar" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000",
"88000") ~ 12,
V4043 == "Empregado do setor público (inclusive empresas de economia mista)" & V4044 %in% c("85011","85012","85013",
"85014","85021","85029",
"86001","86002","86003",
"86004","86009","87000","88000") ~ 12,
########################################################
V4044 %in% c("99000","00000") ~ 0,
.default = NA_integer_)
)
```
## Principal
## Pessoas ocupadas
```{r}
dadosPNADc1VISITA_25PR <- dadosPNADc1VISITA_25 %>%
dplyr::filter(!(is.na(V4013))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_25PR <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_25PR)
dadosPNADc1VISITA_25SRPR <- srvyr::as_survey(dadosPNADc1VISITA_25PR)
```
### Total de Pessoas
```{r}
table_1P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3P_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Secundário
## Pessoas Ocupadas
```{r}
dadosPNADc1VISITA_25SEC <- dadosPNADc1VISITA_25 %>%
dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas")
dadosPNADc1VISITA_25SEC <- PNADcIBGE::pnadc_design(dadosPNADc1VISITA_25SEC)
dadosPNADc1VISITA_25SRSEC <- srvyr::as_survey(dadosPNADc1VISITA_25SEC)
```
### Total de Pessoas
```{r}
table_1S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Habituais
```{r}
table_2S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Total de horas Efetivas
```{r}
table_3S_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(cod_SCN_SEC, Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Total
### Principal
#### Pessoas Ocupadas
```{r}
table_1TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Horas Habituais
```{r}
table_2TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4039,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Horas Efetivas
```{r}
table_3TP_2025 <- dadosPNADc1VISITA_25SRPR %>%
dplyr::filter(V4039C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4039C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Secundário
#### Total de Pessoas
```{r}
table_1TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Habituais
```{r}
table_2TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasHabituais = srvyr::survey_total(V4056,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
#### Total de horas Efetivas
```{r}
table_3TS_2025 <- dadosPNADc1VISITA_25SRSEC %>%
dplyr::filter(V4056C != 0) %>%
dplyr::group_by(Ano) %>%
dplyr::summarise(Qtd_horasEfetivas = srvyr::survey_total(V4056C,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
## Principal & Secundário
### Contagem
```{r}
dadosPNADc_PS_1 <- dadosPNADc1VISITA_25 %>%
#dplyr::filter(!(is.na(V4044))) %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(total = n())
dadosPNADc_PS_2 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_1, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = total)
# %>%
# dplyr::left_join(teste1, by = c("cod_SCN_SEC" = "atividade")) %>%
# dplyr::rename(total_secundario = total)
dadosPNADc_PS_2 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_2)
dadosPNADc_PS_2SV <- srvyr::as_survey(dadosPNADc_PS_2)
table_1PS_2025 <- dadosPNADc_PS_2SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(freq = srvyr::survey_total(vartype = c("se", "ci", "var", "cv")))
```
### Horas habituais
```{r}
dadosPNADc_PS_3 <- dadosPNADc1VISITA_25 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaH = base::sum(V4039, V4056, na.rm = TRUE))
dadosPNADc_PS_4 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_3, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaH)
dadosPNADc_PS_4 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_4)
dadosPNADc_PS_4SV <- srvyr::as_survey(dadosPNADc_PS_4)
table_2PS_2025 <- dadosPNADc_PS_4SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaH = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
### Horas efetivas
```{r}
dadosPNADc_PS_5 <- dadosPNADc1VISITA_25 %>%
dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
tidyr::pivot_longer(cols = c(cod_SCN_PR, cod_SCN_SEC),
names_to = "tipo",
values_to = "atividade") %>%
dplyr::group_by(atividade) %>%
dplyr::summarise(somaE = base::sum(V4039C, V4056C, na.rm = TRUE))
dadosPNADc_PS_6 <- dadosPNADc1VISITA_25 %>%
dplyr::left_join(dadosPNADc_PS_5, by = c("cod_SCN_PR" = "atividade")) %>%
dplyr::rename(total_principal = somaE)
dadosPNADc_PS_6 <- PNADcIBGE::pnadc_design(dadosPNADc_PS_6)
dadosPNADc_PS_6SV <- srvyr::as_survey(dadosPNADc_PS_6)
table_3PS_2025 <- dadosPNADc_PS_6SV %>%
# dplyr::filter(!(is.na(V4044))) %>%
# dplyr::filter(VD4002 == "Pessoas ocupadas") %>%
dplyr::group_by(cod_SCN_PR, Ano) %>%
dplyr::summarise(somaE = srvyr::survey_total(total_principal,
na.rm = TRUE,
vartype = c("se", "ci", "var", "cv")))
```
# Empilhamento
```{r}
table_1TP <- dplyr::bind_rows(table_1TP_2012,
table_1TP_2013,
table_1TP_2014,
table_1TP_2015,
table_1TP_2016,
table_1TP_2017,
table_1TP_2018,
table_1TP_2019,
table_1TP_2020,
table_1TP_2021,
table_1TP_2022,
table_1TP_2023,
table_1TP_2024,
table_1TP_2025
)
table_2TP <- dplyr::bind_rows(table_2TP_2012,
table_2TP_2013,
table_2TP_2014,
table_2TP_2015,
table_2TP_2016,
table_2TP_2017,
table_2TP_2018,
table_2TP_2019,
table_2TP_2020,
table_2TP_2021,
table_2TP_2022,
table_2TP_2023,
table_2TP_2024,
table_2TP_2025
)
table_3TP <- dplyr::bind_rows(table_3TP_2012,
table_3TP_2013,
table_3TP_2014,
table_3TP_2015,
table_3TP_2016,
table_3TP_2017,
table_3TP_2018,
table_3TP_2019,
table_3TP_2020,
table_3TP_2021,
table_3TP_2022,
table_3TP_2023,
table_3TP_2024,
table_3TP_2025
)
table_1TS <- dplyr::bind_rows(table_1TS_2012,
table_1TS_2013,
table_1TS_2014,
table_1TS_2015,
table_1TS_2016,
table_1TS_2017,
table_1TS_2018,
table_1TS_2019,
table_1TS_2020,
table_1TS_2021,
table_1TS_2022,
table_1TS_2023,
table_1TS_2024,
table_1TS_2025
)
table_2TS <- dplyr::bind_rows(table_2TS_2012,
table_2TS_2013,
table_2TS_2014,
table_2TS_2015,
table_2TS_2016,
table_2TS_2017,
table_2TS_2018,
table_2TS_2019,
table_2TS_2020,
table_2TS_2021,
table_2TS_2022,
table_2TS_2023,
table_2TS_2024,
table_2TS_2025
)
table_3TS <- dplyr::bind_rows(table_3TS_2012,
table_3TS_2013,
table_3TS_2014,
table_3TS_2015,
table_3TS_2016,
table_3TS_2017,
table_3TS_2018,
table_3TS_2019,
table_3TS_2020,
table_3TS_2021,
table_3TS_2022,
table_3TS_2023,
table_3TS_2024,
table_3TS_2025
)
table_1P <- dplyr::bind_rows(table_1P_2012,
table_1P_2013,
table_1P_2014,
table_1P_2015,
table_1P_2016,
table_1P_2017,
table_1P_2018,
table_1P_2019,
table_1P_2020,
table_1P_2021,
table_1P_2022,
table_1P_2023,
table_1P_2024,
table_1P_2025
)
table_2P <- dplyr::bind_rows( table_2P_2012,
table_2P_2013,
table_2P_2014,
table_2P_2015,
table_2P_2016,
table_2P_2017,
table_2P_2018,
table_2P_2019,
table_2P_2020,
table_2P_2021,
table_2P_2022,
table_2P_2023,
table_2P_2024,
table_2P_2025
)
table_3P <- dplyr::bind_rows(table_3P_2012,
table_3P_2013,
table_3P_2014,
table_3P_2015,
table_3P_2016,
table_3P_2017,
table_3P_2018,
table_3P_2019,
table_3P_2020,
table_3P_2021,
table_3P_2022,
table_3P_2023,
table_3P_2024,
table_3P_2025
)
table_1S <- dplyr::bind_rows(table_1S_2012,
table_1S_2013,
table_1S_2014,
table_1S_2015,
table_1S_2016,
table_1S_2017,
table_1S_2018,
table_1S_2019,
table_1S_2020,
table_1S_2021,
table_1S_2022,
table_1S_2023,
table_1S_2024,
table_1S_2025
)
table_2S <- dplyr::bind_rows(table_2S_2012,
table_2S_2013,
table_2S_2014,
table_2S_2015,
table_2S_2016,
table_2S_2017,
table_2S_2018,
table_2S_2019,
table_2S_2020,
table_2S_2021,
table_2S_2022,
table_2S_2023,
table_2S_2024,
table_2S_2025
)
table_3S <- dplyr::bind_rows(table_3S_2012,
table_3S_2013,
table_3S_2014,
table_3S_2015,
table_3S_2016,
table_3S_2017,
table_3S_2018,
table_3S_2019,
table_3S_2020,
table_3S_2021,
table_3S_2022,
table_3S_2023,
table_3S_2024,
table_3S_2025
)
table_1PS <- dplyr::bind_rows(table_1PS_2012,
table_1PS_2013,
table_1PS_2014,
table_1PS_2015,
table_1PS_2016,
table_1PS_2017,
table_1PS_2018,
table_1PS_2019,
table_1PS_2020,
table_1PS_2021,
table_1PS_2022,
table_1PS_2023,
table_1PS_2024,
table_1PS_2025
)
table_2PS <- dplyr::bind_rows(table_2PS_2012,
table_2PS_2013,
table_2PS_2014,
table_2PS_2015,
table_2PS_2016,
table_2PS_2017,
table_2PS_2018,
table_2PS_2019,
table_2PS_2020,
table_2PS_2021,
table_2PS_2022,
table_2PS_2023,
table_2PS_2024,
table_2PS_2025
)
table_3PS <- dplyr::bind_rows(table_3PS_2012,
table_3PS_2013,
table_3PS_2014,
table_3PS_2015,
table_3PS_2016,
table_3PS_2017,
table_3PS_2018,
table_3PS_2019,
table_3PS_2020,
table_3PS_2021,
table_3PS_2022,
table_3PS_2023,
table_3PS_2024,
table_3PS_2025
)
```
# Excel
```{r}
sheets <- list("N TOTAL PRINCIPAL" = table_1TP,
"HABITUAL TOTAL PRINCIPAL" = table_2TP,
"EFETIVA TOTAL PRINCIPAL" = table_3TP,
"N TOTAL SECUNDÁRIO" = table_1TS,
"HABITUAL TOTAL SECUNDÁRIO" = table_2TS,
"EFETIVA TOTAL SECUNDÁRIO" = table_3TS,
"N PRINCIPAL" = table_1P,
"HABITUAL PRINCIPAL" = table_2P,
"EFETIVA PRINCIPAL" = table_3P,
"N SECUNDÁRIO" = table_1S,
"HABITUAL SECUNDÁRIO" = table_2S,
"EFETIVA SECUNDÁRIO" = table_3S,
"N P&S" = table_1PS,
"HABITUAL P&S" = table_2PS,
"EFETIVA P&S" = table_3PS)
writexl::write_xlsx(sheets,
paste0("C:/Users/fernanda-romeiro/OneDrive - Governo do Estado do Rio Grande do Sul/Projetos/PNAD/PNAD_projetos/Dados/tabPSTRI_RS_2.xlsx"))
```